Return the consecutive missing weekdays dates and assign rate next to missing dates

Question

Dates       rates
7/26/2019   1.04
7/30/2019   1.0116
7/31/2019   1.005
8/1/2019    1.035
8/2/2019    1.01
8/6/2019    0.9886
8/12/2019   0.965

df = df.merge(
    p         


        

Answer 1

Try option 1 as below which includes creating a new df & merging it (the route you are already on)

or option 2 as suggested by @piRSquared (bfill() instead of ffill())

df['Dates'] = pd.to_datetime(df['Dates'])
a=pd.DataFrame({'Dates':pd.bdate_range('2019-07-26', '2019-08-12')})
df.merge(a, on='Dates', how='outer').sort_values('Dates').bfill().dropna().reset_index(drop=True) 

Output

        Dates   rates
0   2019-07-26  1.0400
1   2019-07-29  1.0116
2   2019-07-30  1.0116
3   2019-07-31  1.0050
4   2019-08-01  1.0350
5   2019-08-02  1.0100
6   2019-08-05  0.9886
7   2019-08-06  0.9886
8   2019-08-07  0.9650
9   2019-08-08  0.9650
10  2019-08-09  0.9650
11  2019-08-12  0.9650

df.set_index('Dates').asfreq('B').bfill().reset_index()

Output

         Dates  rates
0   2019-07-26  1.0400
1   2019-07-29  1.0116
2   2019-07-30  1.0116
3   2019-07-31  1.0050
4   2019-08-01  1.0350
5   2019-08-02  1.0100
6   2019-08-05  0.9886
7   2019-08-06  0.9886
8   2019-08-07  0.9650
9   2019-08-08  0.9650
10  2019-08-09  0.9650
11  2019-08-12  0.9650